Pandas Profiling Report

Dataset statistics

Number of variables	20
Number of observations	338592
Missing cells	2614518
Missing cells (%)	38.6%
Duplicate rows	309470
Duplicate rows (%)	91.4%
Total size in memory	51.7 MiB
Average record size in memory	160.0 B

Variable types

Categorical	8
Numeric	12

Warnings

Dataset has 309470 (91.4%) duplicate rows	Duplicates
`PaySanrenpukuNinki3` is highly correlated with `PaySanrentanKumi1` and 12 other fields	High correlation
`PaySanrentanKumi1` is highly correlated with `PaySanrenpukuNinki3` and 3 other fields	High correlation
`PaySanrentanPay1` is highly correlated with `PaySanrenpukuNinki3` and 4 other fields	High correlation
`PaySanrentanNinki1` is highly correlated with `PaySanrenpukuNinki3` and 4 other fields	High correlation
`PaySanrentanKumi2` is highly correlated with `PaySanrenpukuNinki3` and 3 other fields	High correlation
`PaySanrentanPay2` is highly correlated with `PaySanrenpukuNinki3` and 4 other fields	High correlation
`PaySanrentanNinki2` is highly correlated with `PaySanrenpukuNinki3` and 4 other fields	High correlation
`PaySanrentanKumi3` is highly correlated with `PaySanrenpukuNinki3` and 12 other fields	High correlation
`PaySanrentanPay3` is highly correlated with `PaySanrenpukuNinki3` and 12 other fields	High correlation
`PaySanrentanNinki3` is highly correlated with `PaySanrenpukuNinki3` and 12 other fields	High correlation
`YoubiCD` is highly correlated with `PaySanrenpukuNinki3` and 3 other fields	High correlation
`JyuryoCD` is highly correlated with `PaySanrenpukuNinki3` and 3 other fields	High correlation
`Kyori` is highly correlated with `PaySanrenpukuNinki3` and 3 other fields	High correlation
`TrackCD` is highly correlated with `PaySanrenpukuNinki3` and 3 other fields	High correlation
`KyoriBefore` is highly correlated with `PaySanrentanPay3` and 4 other fields	High correlation
`PaySanrentanPay3` is highly correlated with `KyoriBefore` and 6 other fields	High correlation
`JyuryoCD` is highly correlated with `PaySanrentanPay3` and 3 other fields	High correlation
`PaySanrentanKumi3` is highly correlated with `KyoriBefore` and 6 other fields	High correlation
`PaySanrenpukuNinki3` is highly correlated with `KyoriBefore` and 6 other fields	High correlation
`PaySanrentanNinki3` is highly correlated with `KyoriBefore` and 6 other fields	High correlation
`KigoCD` is highly correlated with `PaySanrentanPay3` and 3 other fields	High correlation
`GradeCD` is highly correlated with `KyoriBefore` and 4 other fields	High correlation
`PaySanrenpukuNinki3` has 338561 (> 99.9%) missing values	Missing
`PaySanrentanKumi2` has 336583 (99.4%) missing values	Missing
`PaySanrentanPay2` has 336583 (99.4%) missing values	Missing
`PaySanrentanNinki2` has 336583 (99.4%) missing values	Missing
`PaySanrentanKumi3` has 338561 (> 99.9%) missing values	Missing
`PaySanrentanPay3` has 338561 (> 99.9%) missing values	Missing
`PaySanrentanNinki3` has 338561 (> 99.9%) missing values	Missing
`GradeCD` has 250525 (74.0%) missing values	Missing
`TokuNum` has 322947 (95.4%) zeros	Zeros
`Nkai` has 322947 (95.4%) zeros	Zeros

Reproduction

Analysis started	2021-04-07 13:01:14.704497
Analysis finished	2021-04-07 13:02:20.931285
Duration	1 minute and 6.23 seconds
Software version	pandas-profiling v2.11.0
Download configuration	config.yaml

PaySanrenpukuNinki3
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	2
Distinct (%)	6.5%
Missing	338561
Missing (%)	> 99.9%
Memory size	2.6 MiB

4.0	18
3.0	13

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	93
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	3.0
2nd row	3.0
3rd row	3.0
4th row	3.0
5th row	3.0

Value	Count	Frequency (%)
4.0	18	< 0.1%
3.0	13	< 0.1%
(Missing)	338561	> 99.9%

Histogram of lengths of the category

Value	Count	Frequency (%)
4.0	18	58.1%
3.0	13	41.9%

Most occurring characters

Value	Count	Frequency (%)
.	31	33.3%
0	31	33.3%
4	18	19.4%
3	13	14.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	62	66.7%
Other Punctuation	31	33.3%

Most frequent character per category

Value	Count	Frequency (%)
0	31	50.0%
4	18	29.0%
3	13	21.0%

Value	Count	Frequency (%)
.	31	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	93	100.0%

Most frequent character per script

Value	Count	Frequency (%)
.	31	33.3%
0	31	33.3%
4	18	19.4%
3	13	14.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	93	100.0%

Most frequent character per block

Value	Count	Frequency (%)
.	31	33.3%
0	31	33.3%
4	18	19.4%
3	13	14.0%

PaySanrentanKumi1
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	3997
Distinct (%)	1.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	80047.02295
Minimum	10203
Maximum	181716
Zeros	0
Zeros (%)	0.0%
Memory size	2.6 MiB

Quantile statistics

Minimum	10203
5-th percentile	11103
Q1	40902
median	80401
Q3	120106
95-th percentile	151614
Maximum	181716
Range	171513
Interquartile range (IQR)	79204

Descriptive statistics

Standard deviation	44893.62243
Coefficient of variation (CV)	0.5608406257
Kurtosis	-1.025950167
Mean	80047.02295
Median Absolute Deviation (MAD)	39589
Skewness	0.184188325
Sum	2.710328159 × 10¹⁰
Variance	2015437335
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
20301	369	0.1%
20104	323	0.1%
40601	318	0.1%
40502	302	0.1%
10402	302	0.1%
10503	300	0.1%
10306	296	0.1%
80709	294	0.1%
40605	289	0.1%
30602	287	0.1%
Other values (3987)	335512	99.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
10203	225	0.1%
10204	237	0.1%
10205	167	< 0.1%
10206	208	0.1%
10207	190	0.1%

Value	Count	Frequency (%)
181716	16	< 0.1%
181715	13	< 0.1%
181714	56	< 0.1%
181710	46	< 0.1%
181709	14	< 0.1%

PaySanrentanPay1
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	13586
Distinct (%)	4.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	158448.6548
Minimum	430
Maximum	27929360
Zeros	0
Zeros (%)	0.0%
Memory size	2.6 MiB

Quantile statistics

Minimum	430
5-th percentile	3280
Q1	11350
median	31970
Q3	103710
95-th percentile	637510
Maximum	27929360
Range	27928930
Interquartile range (IQR)	92360

Descriptive statistics

Standard deviation	570696.2805
Coefficient of variation (CV)	3.601774223
Kurtosis	462.8865925
Mean	158448.6548
Median Absolute Deviation (MAD)	25530
Skewness	15.98290073
Sum	5.364944692 × 10¹⁰
Variance	3.256942446 × 10¹¹
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
4360	198	0.1%
4700	192	0.1%
5650	184	0.1%
4450	184	0.1%
4510	180	0.1%
5170	180	0.1%
5310	178	0.1%
3220	177	0.1%
4010	176	0.1%
10370	171	0.1%
Other values (13576)	336772	99.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
430	20	< 0.1%
450	8	< 0.1%
470	4	< 0.1%
480	17	< 0.1%
500	9	< 0.1%

Value	Count	Frequency (%)
27929360	10	< 0.1%
22946150	12	< 0.1%
21802320	10	< 0.1%
19507010	12	< 0.1%
12995280	13	< 0.1%

PaySanrentanNinki1
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	1894
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	256.3821709
Minimum	1
Maximum	4602
Zeros	0
Zeros (%)	0.0%
Memory size	2.6 MiB

Quantile statistics

Minimum	1
5-th percentile	3
Q1	24
median	93
Q3	296
95-th percentile	1102
Maximum	4602
Range	4601
Interquartile range (IQR)	272

Descriptive statistics

Standard deviation	415.8957262
Coefficient of variation (CV)	1.622171014
Kurtosis	14.27120811
Mean	256.3821709
Median Absolute Deviation (MAD)	83
Skewness	3.257022375
Sum	86808952
Variance	172969.2551
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	6985	2.1%
2	6565	1.9%
3	5353	1.6%
4	5081	1.5%
5	4638	1.4%
7	4146	1.2%
6	3846	1.1%
9	3748	1.1%
8	3681	1.1%
10	3632	1.1%
Other values (1884)	290917	85.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	6985	2.1%
2	6565	1.9%
3	5353	1.6%
4	5081	1.5%
5	4638	1.4%

Value	Count	Frequency (%)
4602	17	< 0.1%
4471	10	< 0.1%
4071	14	< 0.1%
3851	12	< 0.1%
3782	18	< 0.1%

PaySanrentanKumi2
Real number (ℝ_≥0)

HIGH CORRELATION
MISSING

Distinct	164
Distinct (%)	8.2%
Missing	336583
Missing (%)	99.4%
Infinite	0
Infinite (%)	0.0%

Mean	81173.19512
Minimum	10307
Maximum	181702
Zeros	0
Zeros (%)	0.0%
Memory size	2.6 MiB

Quantile statistics

Minimum	10307
5-th percentile	11412.6
Q1	41503
median	80410
Q3	110805
95-th percentile	151309
Maximum	181702
Range	171395
Interquartile range (IQR)	69302

Descriptive statistics

Standard deviation	42835.73805
Coefficient of variation (CV)	0.5277079212
Kurtosis	-0.7256813881
Mean	81173.19512
Median Absolute Deviation (MAD)	30395
Skewness	0.2526079037
Sum	163076949
Variance	1834900455
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
110805	28	< 0.1%
110602	26	< 0.1%
80212	24	< 0.1%
131415	18	< 0.1%
181014	18	< 0.1%
81804	18	< 0.1%
41418	17	< 0.1%
70504	17	< 0.1%
81607	17	< 0.1%
21107	17	< 0.1%
Other values (154)	1809	0.5%
(Missing)	336583	99.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
10307	10	< 0.1%
10403	8	< 0.1%
10607	13	< 0.1%
10608	11	< 0.1%
10711	14	< 0.1%

Value	Count	Frequency (%)
181702	17	< 0.1%
181014	18	< 0.1%
171308	16	< 0.1%
161303	13	< 0.1%
161112	12	< 0.1%

PaySanrentanPay2
Real number (ℝ_≥0)

HIGH CORRELATION
MISSING

Distinct	162
Distinct (%)	8.1%
Missing	336583
Missing (%)	99.4%
Infinite	0
Infinite (%)	0.0%

Mean	91717.59084
Minimum	530
Maximum	1738760
Zeros	0
Zeros (%)	0.0%
Memory size	2.6 MiB

Quantile statistics

Minimum	530
5-th percentile	2790
Q1	7790
median	23570
Q3	70150
95-th percentile	474300
Maximum	1738760
Range	1738230
Interquartile range (IQR)	62360

Descriptive statistics

Standard deviation	221911.2627
Coefficient of variation (CV)	2.419506015
Kurtosis	24.90932199
Mean	91717.59084
Median Absolute Deviation (MAD)	17910
Skewness	4.703103674
Sum	184260640
Variance	4.924460851 × 10¹⁰
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
4210	42	< 0.1%
10280	26	< 0.1%
32000	21	< 0.1%
8750	18	< 0.1%
73430	18	< 0.1%
72920	18	< 0.1%
9840	17	< 0.1%
9910	17	< 0.1%
3420	17	< 0.1%
24290	17	< 0.1%
Other values (152)	1798	0.5%
(Missing)	336583	99.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
530	4	< 0.1%
580	5	< 0.1%
590	8	< 0.1%
620	7	< 0.1%
850	6	< 0.1%

Value	Count	Frequency (%)
1738760	8	< 0.1%
1400230	14	< 0.1%
1268270	15	< 0.1%
760340	16	< 0.1%
676080	16	< 0.1%

PaySanrentanNinki2
Real number (ℝ_≥0)

HIGH CORRELATION
MISSING

Distinct	134
Distinct (%)	6.7%
Missing	336583
Missing (%)	99.4%
Infinite	0
Infinite (%)	0.0%

Mean	325.8760577
Minimum	1
Maximum	3404
Zeros	0
Zeros (%)	0.0%
Memory size	2.6 MiB

Quantile statistics

Minimum	1
5-th percentile	6
Q1	37
median	141
Q3	369
95-th percentile	1227
Maximum	3404
Range	3403
Interquartile range (IQR)	332

Descriptive statistics

Standard deviation	517.3715154
Coefficient of variation (CV)	1.587632792
Kurtosis	14.89011922
Mean	325.8760577
Median Absolute Deviation (MAD)	119
Skewness	3.45410245
Sum	654685
Variance	267673.2849
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
6	44	< 0.1%
13	44	< 0.1%
113	39	< 0.1%
21	30	< 0.1%
22	29	< 0.1%
53	28	< 0.1%
127	28	< 0.1%
17	27	< 0.1%
68	26	< 0.1%
28	26	< 0.1%
Other values (124)	1688	0.5%
(Missing)	336583	99.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	22	< 0.1%
2	13	< 0.1%
3	6	< 0.1%
4	24	< 0.1%
6	44	< 0.1%

Value	Count	Frequency (%)
3404	16	< 0.1%
3053	16	< 0.1%
1963	15	< 0.1%
1805	8	< 0.1%
1567	15	< 0.1%

PaySanrentanKumi3
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	2
Distinct (%)	6.5%
Missing	338561
Missing (%)	> 99.9%
Memory size	2.6 MiB

81811.0	18
60514.0	13

Length

Max length	7
Median length	7
Mean length	7
Min length	7

Characters and Unicode

Total characters	217
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	60514.0
2nd row	60514.0
3rd row	60514.0
4th row	60514.0
5th row	60514.0

Value	Count	Frequency (%)
81811.0	18	< 0.1%
60514.0	13	< 0.1%
(Missing)	338561	> 99.9%

Histogram of lengths of the category

Value	Count	Frequency (%)
81811.0	18	58.1%
60514.0	13	41.9%

Most occurring characters

Value	Count	Frequency (%)
1	67	30.9%
0	44	20.3%
8	36	16.6%
.	31	14.3%
6	13	6.0%
5	13	6.0%
4	13	6.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	186	85.7%
Other Punctuation	31	14.3%

Most frequent character per category

Value	Count	Frequency (%)
1	67	36.0%
0	44	23.7%
8	36	19.4%
6	13	7.0%
5	13	7.0%
4	13	7.0%

Value	Count	Frequency (%)
.	31	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	217	100.0%

Most frequent character per script

Value	Count	Frequency (%)
1	67	30.9%
0	44	20.3%
8	36	16.6%
.	31	14.3%
6	13	6.0%
5	13	6.0%
4	13	6.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	217	100.0%

Most frequent character per block

Value	Count	Frequency (%)
1	67	30.9%
0	44	20.3%
8	36	16.6%
.	31	14.3%
6	13	6.0%
5	13	6.0%
4	13	6.0%

PaySanrentanPay3
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	2
Distinct (%)	6.5%
Missing	338561
Missing (%)	> 99.9%
Memory size	2.6 MiB

5410.0	18
4620.0	13

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	186
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	4620.0
2nd row	4620.0
3rd row	4620.0
4th row	4620.0
5th row	4620.0

Value	Count	Frequency (%)
5410.0	18	< 0.1%
4620.0	13	< 0.1%
(Missing)	338561	> 99.9%

Histogram of lengths of the category

Value	Count	Frequency (%)
5410.0	18	58.1%
4620.0	13	41.9%

Most occurring characters

Value	Count	Frequency (%)
0	62	33.3%
4	31	16.7%
.	31	16.7%
5	18	9.7%
1	18	9.7%
6	13	7.0%
2	13	7.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	155	83.3%
Other Punctuation	31	16.7%

Most frequent character per category

Value	Count	Frequency (%)
0	62	40.0%
4	31	20.0%
5	18	11.6%
1	18	11.6%
6	13	8.4%
2	13	8.4%

Value	Count	Frequency (%)
.	31	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	186	100.0%

Most frequent character per script

Value	Count	Frequency (%)
0	62	33.3%
4	31	16.7%
.	31	16.7%
5	18	9.7%
1	18	9.7%
6	13	7.0%
2	13	7.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	186	100.0%

Most frequent character per block

Value	Count	Frequency (%)
0	62	33.3%
4	31	16.7%
.	31	16.7%
5	18	9.7%
1	18	9.7%
6	13	7.0%
2	13	7.0%

PaySanrentanNinki3
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	2
Distinct (%)	6.5%
Missing	338561
Missing (%)	> 99.9%
Memory size	2.6 MiB

14.0	18
26.0	13

Length

Max length	4
Median length	4
Mean length	4
Min length	4

Characters and Unicode

Total characters	124
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	26.0
2nd row	26.0
3rd row	26.0
4th row	26.0
5th row	26.0

Value	Count	Frequency (%)
14.0	18	< 0.1%
26.0	13	< 0.1%
(Missing)	338561	> 99.9%

Histogram of lengths of the category

Value	Count	Frequency (%)
14.0	18	58.1%
26.0	13	41.9%

Most occurring characters

Value	Count	Frequency (%)
.	31	25.0%
0	31	25.0%
1	18	14.5%
4	18	14.5%
2	13	10.5%
6	13	10.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	93	75.0%
Other Punctuation	31	25.0%

Most frequent character per category

Value	Count	Frequency (%)
0	31	33.3%
1	18	19.4%
4	18	19.4%
2	13	14.0%
6	13	14.0%

Value	Count	Frequency (%)
.	31	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	124	100.0%

Most frequent character per script

Value	Count	Frequency (%)
.	31	25.0%
0	31	25.0%
1	18	14.5%
4	18	14.5%
2	13	10.5%
6	13	10.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	124	100.0%

Most frequent character per block

Value	Count	Frequency (%)
.	31	25.0%
0	31	25.0%
1	18	14.5%
4	18	14.5%
2	13	10.5%
6	13	10.5%

YoubiCD
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	8
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	1.645511412
Minimum	1
Maximum	8
Zeros	0
Zeros (%)	0.0%
Memory size	2.6 MiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	2
Q3	2
95-th percentile	3
Maximum	8
Range	7
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	0.7493408244
Coefficient of variation (CV)	0.455384763
Kurtosis	11.88427302
Mean	1.645511412
Median Absolute Deviation (MAD)	1
Skewness	2.238450502
Sum	557157
Variance	0.5615116711
Monotocity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
2	157548	46.5%
1	155859	46.0%
3	19804	5.8%
4	2958	0.9%
5	1015	0.3%
7	837	0.2%
8	299	0.1%
6	272	0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	155859	46.0%
2	157548	46.5%
3	19804	5.8%
4	2958	0.9%
5	1015	0.3%

Value	Count	Frequency (%)
8	299	0.1%
7	837	0.2%
6	272	0.1%
5	1015	0.3%
4	2958	0.9%

TokuNum
Real number (ℝ_≥0)

ZEROS

Distinct	141
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	4.137808926
Minimum	0
Maximum	212
Zeros	322947
Zeros (%)	95.4%
Memory size	2.6 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	212
Range	212
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	22.77716081
Coefficient of variation (CV)	5.504642968
Kurtosis	39.92066535
Mean	4.137808926
Median Absolute Deviation (MAD)	0
Skewness	6.1903803
Sum	1401029
Variance	518.7990546
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	322947	95.4%
19	183	0.1%
11	181	0.1%
14	179	0.1%
1	176	0.1%
18	171	0.1%
7	162	< 0.1%
13	162	< 0.1%
92	161	< 0.1%
78	160	< 0.1%
Other values (131)	14110	4.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	322947	95.4%
1	176	0.1%
2	134	< 0.1%
3	136	< 0.1%
4	117	< 0.1%

Value	Count	Frequency (%)
212	14	< 0.1%
211	15	< 0.1%
210	14	< 0.1%
209	42	< 0.1%
208	76	< 0.1%

Nkai
Real number (ℝ_≥0)

ZEROS

Distinct	139
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	2.106169077
Minimum	0
Maximum	162
Zeros	322947
Zeros (%)	95.4%
Memory size	2.6 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	162
Range	162
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	11.34855447
Coefficient of variation (CV)	5.38824475
Kurtosis	58.02974961
Mean	2.106169077
Median Absolute Deviation (MAD)	0
Skewness	6.862258032
Sum	713132
Variance	128.7896885
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	322947	95.4%
53	375	0.1%
55	359	0.1%
63	342	0.1%
17	342	0.1%
52	325	0.1%
54	325	0.1%
18	310	0.1%
56	309	0.1%
58	303	0.1%
Other values (129)	12655	3.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	322947	95.4%
1	86	< 0.1%
2	90	< 0.1%
3	102	< 0.1%
4	80	< 0.1%

Value	Count	Frequency (%)
162	12	< 0.1%
161	13	< 0.1%
160	16	< 0.1%
159	13	< 0.1%
158	11	< 0.1%

GradeCD
Categorical

HIGH CORRELATION
MISSING

Distinct	9
Distinct (%)	< 0.1%
Missing	250525
Missing (%)	74.0%
Memory size	2.6 MiB

E	71024
C	6880
B	4166
A	3394
L	1398
Other values (4)	1205

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	88067
Distinct characters	9
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	E
2nd row	E
3rd row	E
4th row	E
5th row	E

Value	Count	Frequency (%)
E	71024	21.0%
C	6880	2.0%
B	4166	1.2%
A	3394	1.0%
L	1398	0.4%
H	513	0.2%
G	337	0.1%
F	234	0.1%
D	121	< 0.1%
(Missing)	250525	74.0%

Histogram of lengths of the category

Value	Count	Frequency (%)
e	71024	80.6%
c	6880	7.8%
b	4166	4.7%
a	3394	3.9%
l	1398	1.6%
h	513	0.6%
g	337	0.4%
f	234	0.3%
d	121	0.1%

Most occurring characters

Value	Count	Frequency (%)
E	71024	80.6%
C	6880	7.8%
B	4166	4.7%
A	3394	3.9%
L	1398	1.6%
H	513	0.6%
G	337	0.4%
F	234	0.3%
D	121	0.1%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	88067	100.0%

Most frequent character per category

Value	Count	Frequency (%)
E	71024	80.6%
C	6880	7.8%
B	4166	4.7%
A	3394	3.9%
L	1398	1.6%
H	513	0.6%
G	337	0.4%
F	234	0.3%
D	121	0.1%

Most occurring scripts

Value	Count	Frequency (%)
Latin	88067	100.0%

Most frequent character per script

Value	Count	Frequency (%)
E	71024	80.6%
C	6880	7.8%
B	4166	4.7%
A	3394	3.9%
L	1398	1.6%
H	513	0.6%
G	337	0.4%
F	234	0.3%
D	121	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	88067	100.0%

Most frequent character per block

Value	Count	Frequency (%)
E	71024	80.6%
C	6880	7.8%
B	4166	4.7%
A	3394	3.9%
L	1398	1.6%
H	513	0.6%
G	337	0.4%
F	234	0.3%
D	121	0.1%

SyubetuCD
Real number (ℝ_≥0)

Distinct	6
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	12.73259557
Minimum	11
Maximum	19
Zeros	0
Zeros (%)	0.0%
Memory size	2.6 MiB

Quantile statistics

Minimum	11
5-th percentile	11
Q1	12
median	13
Q3	13
95-th percentile	14
Maximum	19
Range	8
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.480650616
Coefficient of variation (CV)	0.1162881996
Kurtosis	5.517360522
Mean	12.73259557
Median Absolute Deviation (MAD)	1
Skewness	1.862398938
Sum	4311155
Variance	2.192326245
Monotocity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
12	108174	31.9%
13	89410	26.4%
14	70494	20.8%
11	58656	17.3%
18	6697	2.0%
19	5161	1.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
11	58656	17.3%
12	108174	31.9%
13	89410	26.4%
14	70494	20.8%
18	6697	2.0%

Value	Count	Frequency (%)
19	5161	1.5%
18	6697	2.0%
14	70494	20.8%
13	89410	26.4%
12	108174	31.9%

KigoCD
Categorical

HIGH CORRELATION

Distinct	31
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.6 MiB

A03	120825
003	81074
023	40734
A04	25424
A00	25137
Other values (26)	45398

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	1015776
Distinct characters	8
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	A03
2nd row	A04
3rd row	A04
4th row	A03
5th row	A03

Value	Count	Frequency (%)
A03	120825	35.7%
003	81074	23.9%
023	40734	12.0%
A04	25424	7.5%
A00	25137	7.4%
000	11795	3.5%
N04	6258	1.8%
N01	5979	1.8%
020	5503	1.6%
N03	3000	0.9%
Other values (21)	12863	3.8%

Histogram of lengths of the category

Value	Count	Frequency (%)
a03	120825	35.7%
003	81074	23.9%
023	40734	12.0%
a04	25424	7.5%
a00	25137	7.4%
000	11795	3.5%
n04	6258	1.8%
n01	5979	1.8%
020	5503	1.6%
n03	3000	0.9%
Other values (21)	12863	3.8%

Most occurring characters

Value	Count	Frequency (%)
0	472178	46.5%
3	246900	24.3%
A	173457	17.1%
2	54578	5.4%
4	37131	3.7%
N	20881	2.1%
1	10058	1.0%
M	593	0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	820845	80.8%
Uppercase Letter	194931	19.2%

Most frequent character per category

Value	Count	Frequency (%)
0	472178	57.5%
3	246900	30.1%
2	54578	6.6%
4	37131	4.5%
1	10058	1.2%

Value	Count	Frequency (%)
A	173457	89.0%
N	20881	10.7%
M	593	0.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	820845	80.8%
Latin	194931	19.2%

Most frequent character per script

Value	Count	Frequency (%)
0	472178	57.5%
3	246900	30.1%
2	54578	6.6%
4	37131	4.5%
1	10058	1.2%

Value	Count	Frequency (%)
A	173457	89.0%
N	20881	10.7%
M	593	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1015776	100.0%

Most frequent character per block

Value	Count	Frequency (%)
0	472178	46.5%
3	246900	24.3%
A	173457	17.1%
2	54578	5.4%
4	37131	3.7%
N	20881	2.1%
1	10058	1.0%
M	593	0.1%

JyuryoCD
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.6 MiB

3	162725
4	138594
1	20984
2	16289

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	338592
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	4
3rd row	4
4th row	1
5th row	1

Value	Count	Frequency (%)
3	162725	48.1%
4	138594	40.9%
1	20984	6.2%
2	16289	4.8%

Histogram of lengths of the category

Value	Count	Frequency (%)
3	162725	48.1%
4	138594	40.9%
1	20984	6.2%
2	16289	4.8%

Most occurring characters

Value	Count	Frequency (%)
3	162725	48.1%
4	138594	40.9%
1	20984	6.2%
2	16289	4.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	338592	100.0%

Most frequent character per category

Value	Count	Frequency (%)
3	162725	48.1%
4	138594	40.9%
1	20984	6.2%
2	16289	4.8%

Most occurring scripts

Value	Count	Frequency (%)
Common	338592	100.0%

Most frequent character per script

Value	Count	Frequency (%)
3	162725	48.1%
4	138594	40.9%
1	20984	6.2%
2	16289	4.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	338592	100.0%

Most frequent character per block

Value	Count	Frequency (%)
3	162725	48.1%
4	138594	40.9%
1	20984	6.2%
2	16289	4.8%

Kyori
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	49
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	1655.659082
Minimum	1000
Maximum	4260
Zeros	0
Zeros (%)	0.0%
Memory size	2.6 MiB

Quantile statistics

Minimum	1000
5-th percentile	1200
Q1	1400
median	1600
Q3	1800
95-th percentile	2400
Maximum	4260
Range	3260
Interquartile range (IQR)	400

Descriptive statistics

Standard deviation	428.5184892
Coefficient of variation (CV)	0.2588204865
Kurtosis	3.330046133
Mean	1655.659082
Median Absolute Deviation (MAD)	200
Skewness	1.406640369
Sum	560592920
Variance	183628.0956
Monotocity	Not monotonic

Histogram with fixed size bins (bins=49)

Value	Count	Frequency (%)
1800	78345	23.1%
1200	69466	20.5%
1400	55219	16.3%
1600	44069	13.0%
2000	29701	8.8%
1700	13212	3.9%
2400	7402	2.2%
2200	6591	1.9%
1000	6436	1.9%
1900	3776	1.1%
Other values (39)	24375	7.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1000	6436	1.9%
1150	1408	0.4%
1200	69466	20.5%
1300	3365	1.0%
1400	55219	16.3%

Value	Count	Frequency (%)
4260	11	< 0.1%
4250	110	< 0.1%
4100	113	< 0.1%
3930	116	< 0.1%
3900	133	< 0.1%

KyoriBefore
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.6 MiB

0	338582
2000	10

Length

Max length	4
Median length	1
Mean length	1.000088602
Min length	1

Characters and Unicode

Total characters	338622
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Value	Count	Frequency (%)
0	338582	> 99.9%
2000	10	< 0.1%

Histogram of lengths of the category

Value	Count	Frequency (%)
0	338582	> 99.9%
2000	10	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	338612	> 99.9%
2	10	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	338622	100.0%

Most frequent character per category

Value	Count	Frequency (%)
0	338612	> 99.9%
2	10	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	338622	100.0%

Most frequent character per script

Value	Count	Frequency (%)
0	338612	> 99.9%
2	10	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	338622	100.0%

Most frequent character per block

Value	Count	Frequency (%)
0	338612	> 99.9%
2	10	< 0.1%

TrackCD
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	13
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	20.90511294
Minimum	10
Maximum	57
Zeros	0
Zeros (%)	0.0%
Memory size	2.6 MiB

Quantile statistics

Minimum	10
5-th percentile	11
Q1	17
median	23
Q3	24
95-th percentile	24
Maximum	57
Range	47
Interquartile range (IQR)	7

Descriptive statistics

Standard deviation	7.666498496
Coefficient of variation (CV)	0.3667283941
Kurtosis	8.530745825
Mean	20.90511294
Median Absolute Deviation (MAD)	1
Skewness	2.30592168
Sum	7078304
Variance	58.77519919
Monotocity	Not monotonic

Histogram with fixed size bins (bins=13)

Value	Count	Frequency (%)
24	119996	35.4%
17	65207	19.3%
23	51257	15.1%
11	44554	13.2%
18	40557	12.0%
52	6182	1.8%
54	4362	1.3%
12	3634	1.1%
10	1394	0.4%
56	997	0.3%
Other values (3)	452	0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
10	1394	0.4%
11	44554	13.2%
12	3634	1.1%
17	65207	19.3%
18	40557	12.0%

Value	Count	Frequency (%)
57	94	< 0.1%
56	997	0.3%
55	223	0.1%
54	4362	1.3%
52	6182	1.8%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	PaySanrenpukuNinki3	PaySanrentanKumi1	PaySanrentanPay1	PaySanrentanNinki1	PaySanrentanKumi2	PaySanrentanPay2	PaySanrentanNinki2	PaySanrentanKumi3	PaySanrentanPay3	PaySanrentanNinki3	YoubiCD	GradeCD	SyubetuCD	KigoCD	JyuryoCD	Kyori	TrackCD
0	nan	161505	15490	27	nan	nan	nan	nan	nan	nan	1	E	13	A03	1	1200	17
1	nan	80901	4130	3	nan	nan	nan	nan	nan	nan	1	E	13	A04	4	1200	17
2	nan	40805	3180	3	nan	nan	nan	nan	nan	nan	2	E	13	A04	4	1200	17
3	nan	151606	731480	1833	nan	nan	nan	nan	nan	nan	3	E	14	A03	1	1200	11
4	nan	161505	15490	27	nan	nan	nan	nan	nan	nan	1	E	13	A03	1	1200	17
5	nan	91216	44600	136	nan	nan	nan	nan	nan	nan	2	E	13	A04	4	1200	17
6	nan	10812	310660	672	nan	nan	nan	nan	nan	nan	1	E	13	A03	4	1200	17
7	nan	160607	23430	55	nan	nan	nan	nan	nan	nan	1	NaN	14	003	4	1200	17
8	nan	141612	3015110	2280	nan	nan	nan	nan	nan	nan	2	E	14	000	1	1200	17
9	nan	140811	6330	4	nan	nan	nan	nan	nan	nan	2	NaN	14	003	4	1200	11

Last rows

	PaySanrenpukuNinki3	PaySanrentanKumi1	PaySanrentanPay1	PaySanrentanNinki1	PaySanrentanKumi2	PaySanrentanPay2	PaySanrentanNinki2	PaySanrentanKumi3	PaySanrentanPay3	PaySanrentanNinki3	YoubiCD	GradeCD	SyubetuCD	KigoCD	JyuryoCD	Kyori	TrackCD
338582	nan	20508	4340	7	nan	nan	nan	nan	nan	nan	1	E	11	M01	2	1200	17
338583	nan	20508	4340	7	nan	nan	nan	nan	nan	nan	1	E	11	M01	2	1200	17
338584	nan	21301	83220	263	nan	nan	nan	nan	nan	nan	2	NaN	12	023	3	1200	17
338585	nan	81506	373540	900	nan	nan	nan	nan	nan	nan	2	NaN	12	023	3	2000	17
338586	nan	40212	14520	28	nan	nan	nan	nan	nan	nan	2	NaN	13	A03	4	1000	24
338587	nan	100801	39160	127	nan	nan	nan	nan	nan	nan	2	NaN	13	004	4	1200	17
338588	nan	100602	13830	34	nan	nan	nan	nan	nan	nan	2	E	13	N01	2	1800	17
338589	nan	71406	6500	9	nan	nan	nan	nan	nan	nan	2	NaN	11	A03	3	1200	17
338590	nan	50904	280990	613	nan	nan	nan	nan	nan	nan	2	NaN	12	003	3	2000	17
338591	nan	100914	173200	453	nan	nan	nan	nan	nan	nan	2	NaN	11	A03	3	1800	17

Most frequent

	PaySanrenpukuNinki3	PaySanrentanKumi1	PaySanrentanPay1	PaySanrentanNinki1	PaySanrentanKumi2	PaySanrentanPay2	PaySanrentanNinki2	PaySanrentanKumi3	PaySanrentanPay3	PaySanrentanNinki3	YoubiCD	TokuNum	Nkai	GradeCD	SyubetuCD	KigoCD	JyuryoCD	Kyori	KyoriBefore	TrackCD	count
0	3.00	60502	6880	51	60,508.00	13,310.00	109.00	60,514.00	4,620.00	26.00	1	0	0	E	13	A04	1	1200	0	24	13

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Interactions

Correlations

Pearson's r

Spearman's ρ

Kendall's τ

Phik (φk)

Cramér's V (φc)

Missing values

Sample

First rows

Last rows

Duplicate rows

Most frequent